Knowledge Base Concepts in the KEA System Combined with Social Networking Techniques

Nicole Natho (), Sabina Jeschke, Marc Wilke and Olivier Pfeiffer
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Nicole Natho: MuLF, TU Berlin
Sabina Jeschke: IMA/ZLW & IfU - RWTH Aachen University
Marc Wilke: Institute of Information Technology Services (IITS), University of Stuttgart
Olivier Pfeiffer: MuLF, Berlin University of Technology

A chapter in Automation, Communication and Cybernetics in Science and Engineering 2009/2010, 2011, pp 635-650 from Springer

Abstract: Abstract We present a knowledge management system for mathematics suggesting a combination of an information retrieval system with social networking techniques to overcome information flood in mathematical and natural scientific texts, and problems of merging databases within the system to structure our data efficiently. With regard to the increasing demand of knowledge management systems in all fields, especially mathematical knowledge management systems remain a major challenge. Particularly systems that automatically extract information using natural language processing methods require a very different semantic analysis of texts than other field specific languages. In this regard, a numerous number of information fragments has to be extracted based on the specifics of the underlying text structures. New concepts are needed to control this information flood. One possible approach is the use of social network techniques.

Keywords: Knowledge based system; knowledge management; natural language processing; social networking (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-16208-4_55

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DOI: 10.1007/978-3-642-16208-4_55

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